Conclusion The proposed method effectively reduces dimensionality. Additionally, if the symbolic transformation includes the right domain knowledge, the method arguably outputs a data representation that denotes the relevant domain concepts more clearly. The method is capable of finding patterns in BAEPs time series and is very accurate at correctly predicting whether or not new patients have an auditory-related disorder.

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Conclusion: Based on these results NDDS is considered to be an applicable instrument for identifying personality pathology in patients with depressive symptoms, by recognizing the specific pattern. This is thought to be important for adequate treatment planning.
PMID: 31517547 [PubMed - as supplied by publisher]

CONCLUSIONS Our results demonstrated a regulation loop among MATAL1, miR-194, and YAP1, which dynamically regulates the progression of AP, providing a new therapeutic target for treatment of this disease.
PMID: 31518341 [PubMed - in process]